Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use will702/stockbit-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use will702/stockbit-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="will702/stockbit-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("will702/stockbit-sentiment") model = AutoModelForSequenceClassification.from_pretrained("will702/stockbit-sentiment") - Notebooks
- Google Colab
- Kaggle
| { | |
| "label_map": { | |
| "Positif": 0, | |
| "Netral": 1, | |
| "Negatif": 2 | |
| }, | |
| "split": { | |
| "train_rows": 21598, | |
| "eval_rows": 5400, | |
| "eval_source": "public_stratified_20_percent", | |
| "test_size": 0.2, | |
| "random_state": 42, | |
| "stratify": "label" | |
| }, | |
| "svm": { | |
| "Negatif": { | |
| "precision": 0.8167358229598893, | |
| "recall": 0.77088772845953, | |
| "f1-score": 0.7931497649429147, | |
| "support": 1532.0 | |
| }, | |
| "Netral": { | |
| "precision": 0.7832957110609481, | |
| "recall": 0.7711111111111111, | |
| "f1-score": 0.7771556550951848, | |
| "support": 1350.0 | |
| }, | |
| "Positif": { | |
| "precision": 0.8483809523809523, | |
| "recall": 0.8844320889594917, | |
| "f1-score": 0.8660314991250243, | |
| "support": 2518.0 | |
| }, | |
| "accuracy": 0.8238888888888889, | |
| "macro avg": { | |
| "precision": 0.8161374954672632, | |
| "recall": 0.8088103095100442, | |
| "f1-score": 0.8121123063877079, | |
| "support": 5400.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.8231318016300128, | |
| "recall": 0.8238888888888889, | |
| "f1-score": 0.8231357201977512, | |
| "support": 5400.0 | |
| } | |
| }, | |
| "random_forest": { | |
| "Negatif": { | |
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| "recall": 0.7016971279373369, | |
| "f1-score": 0.7322888283378747, | |
| "support": 1532.0 | |
| }, | |
| "Netral": { | |
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| "recall": 0.717037037037037, | |
| "f1-score": 0.7364016736401674, | |
| "support": 1350.0 | |
| }, | |
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| "recall": 0.8788721207307387, | |
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| "macro avg": { | |
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| "weighted avg": { | |
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| "recall": 0.7881481481481482, | |
| "f1-score": 0.7860898431879371, | |
| "support": 5400.0 | |
| } | |
| } | |
| } |